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Episode 14 - Practical Data Structures: Ordered Indexes vs Hash Tables

13 mins
2020-06-14 engineering
Hash tables are data structures that map keys into values. Used in Python’s dicts, Go’s maps, Java’s HashMaps, and other places. However in databases, the default structure is almost always an ordered index, typically a B-Tree. Hash tables use a fast and repeatable hash function to assign each key a unique place in memory to store its values (sometimes called buckets). The load factor is the number of entries occupied in the table, divided by the number of unique storage buckets. Continue reading

Uniquely Managing Test Execution Resources using WebSockets

Executing tests for simple applications is complicated. You have to think about the users, how they interact with it, how those interactions propagate through different components, as well as how to handle error situations gracefully. But things get even more complicated when you start looking at more extensive systems, like those with multiple external dependencies.

Dependencies come in various forms, including third-party modules, cloud services, compute resources, networks, and others.

This level of complexity is standard in almost all projects involving a large organization, whether delivering internal tools or external products.

It means you must put emphasis on developing test systems and mechanisms good enough to validate not just code, but those third-party dependencies as well. After all, they’re part of the final product and failing to interact with them, means the product fails.

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12 Trending Alternatives for Distributing Python Applications in 2020

One of the more prevalent topics in the Python ecosystem of 2019 was that of packaging and distribution. As the year comes to an end, I wanted to put together a summary of the many paths we currently have available to distribute apps built with Python. Though some of these also apply to any language.

Whether delivering an executable, a virtual environment, your packaged code, or a full application, the following list includes both standard systems and some up-and-comers to keep in mind as we enter 2020.

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Unconventional Secure and Asynchronous RESTful APIs using SSH

Some time ago, in a desperate search for asynchronicity, I came across a Python package that changed the way I look at remote interfaces: AsyncSSH.

Reading through their documentation and example code, you’ll find an interesting assortment of use cases. All of which take advantage of the authentication and encryption capabilities of SSH, while using Python’s asyncio to handle asynchronous communications.

Thinking about various applications I’ve developed over the years, many included functions that could benefit from decoupling into separate services. But at times, I would avoid it due to security implications.

I wanted to build informative dashboards that optimize maintenance tasks. But they bypassed business logic, so I wouldn’t dare expose them over the same interfaces. I even looked at using HTTPS client certs, but support from REST frameworks seemed limited.

I realized that asyncssh could provide the extra security I was looking for over a well known key-based system. And in my never-ending quest to find what makes things tick, I decided to take a stab at writing a REST-ish service over SSH.

A great way to familiarize myself with the library and the protocol, it helped me learn more about building asynchronous apps, creating a small framework called korv.

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Practical Log Viewers with Sanic and Elasticsearch - Designing CI/CD Systems

One of the critical pieces in a build system is the ability to view build and test output. Not only does it track progress as the build transitions through the various phases, it’s also an instrument for debugging.

This chapter in the continuous builds series covers how to build a simple log viewer. You’ll find details on retrieving log entries from Docker containers, serving them through Python, linking from a GitHub pull request, and highlighting the data for easy reading.

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